Introduction to RNA-seq data analysis
27th - 29th March 2019
Bioinformatics Training Room, Craik-Marshall Building, Downing Site, University of Cambridge
Outline
In this workshop, you will be learning how to analyse RNA-seq data. This will include read alignment, quality control, de-novo transcriptome assembly, quantification against a reference, reading the count data into R, performing differential expression analysis, and gene set testing, with a focus on the DESeq2 analysis workflow. You will learn how to generate common plots for analysis and visualisation of gene expression data, such as boxplots and heatmaps.
This workshop is aimed at biologists interested in learning how to perform differential expression analysis of RNA-seq data.
Etherpad
There is a course Etherpad. Please post questions here and we will answer them as soon as we can (or if you can answer someone elses question do so!). The trainers may also post useful code snippets here for you.
Instructors
- Stephane Ballereau - Bioinformatics Core, Cancer Research UK Cambridge Institute
- Dominique-Laurent Couturier - Bioinformatics Core, Cancer Research UK Cambridge Institute
- Abbi Edwards - Bioinformatics Core, Cancer Research UK Cambridge Institute
- Yasin Memari - Medical Genetics and MRC Cancer Unit, University of Cambridge
- Guillermo Parada González - Wellcome Sanger Institue and Wellcome Trust/ Cancer Research UK Gurdon Institute, University of Cambridge
- Ashley D Sawle - Bioinformatics Core, Cancer Research UK Cambridge Institute
Timetable
Day 1
9:30 - 10:15 - Introduction to RNAseq Methods - Ashley Sawle
10:15 - 10:45 - Introduction to Alignment and Quantification - Guillermo Parada Gonzalez
10:30 - 12:30 Practical: Basic Unix, input file formats and quality control
12:30 - 13:30 Lunch
13:30 - 16:00 Practical: Mapping reads to the genome and getting raw counts
16:00 - 17:30 Practical: Introduction to reporducible bioinformatics
Day 2
9:30 - 10:00 Practial: Connecting snakemake workflows
10:00 - 11:15 Practical: Guided transcriptome assembly using StringTie
11:15 - 12:30 Practical: Alternative splicing analysis using Whippet
12:30 - 13:30 - Lunch
13:30 - 14:00 - Introduction to RNAseq Analysis in R - Ashley Sawle
14:00 - 14:45 - RNA-seq Pre-processing - Ashley Sawle
14:45 - 17:30 - Linear Model and Statistics for Differential Expression - Dominique-Laurent Couturier
Day 3
9:30 - 12:00 - Differential Expression for RNA-seq - Stephane Ballereau
12:00 - 13:00 Lunch
13:00 - 15:30 Annotation and Visualisation of RNA-seq results - Abbi Edwards
15:30 - 17:30 Gene-set testing - Ashley Sawle
Prerequisites
**Some basic R knowledge is assumed (and is essential). Without it, you will struggle on this course.** If you are not familiar with the R statistical programming language we strongly encourage you to work through an introductory R course before attempting these materials. We recommend reading our R crash course before attending, which should take around 1 hour
Running these materials on your own computer.
- You can of course start from a base R & Rstudio setup but you may find it easier to pull a Docker container image onto your Linux, Mac or Windows machine (You will need to install Docker and for Win & Mac we also recommend the Kitematic graphical interface to Docker. The image is pullable using ‘docker pull mfernandes61/crukci_rnaseq_course’ or searching for ‘mfernandes61/crukci_rnaseq_course’ in Kitematic.
Source Materials for Practicals
The all of the lecture slides and other source materials, including R code and practical solutions, can be found in the course’s Github repository
Supplementary lessons
Introductory R materials:
Additional RNAseq materials:
Data: Example Mouse mammary data (fastq files): https://figshare.com/s/f5d63d8c265a05618137
Additional resources
Bioconductor help
Biostars
SEQanswers
Acknowledgements
This course is based on the course RNAseq analysis in R prepared by Combine Australia and delivered on May 11/12th 2016 in Carlton. We are extremely grateful to the authors for making their materials available; Maria Doyle, Belinda Phipson, Matt Ritchie, Anna Trigos, Harriet Dashnow, Charity Law.
